Methods – Page 5 – Integration and Implementation Insights

Citizen science and participatory modeling

February 14, 2024February 2, 2017

By Rebecca Jordan and Steven Gray

authors_rebecca-jordan_steven-gray — 1. Rebecca Jordan (biography)
2. Steven Gray (biography)

As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?

Let us start with definitions. Citizen science has been defined in many ways, but we will keep the definition simple. Citizen science refers to endeavors where persons who do not consider themselves scientific experts work with those who do consider themselves experts (around a specific issue) to address an authentic research question.

Dealing with deep uncertainty: Scenarios

October 25, 2022January 5, 2017

By Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present.

Two barriers to interdisciplinary thinking in the public sector and how time graphs can help

September 5, 2024December 21, 2016

By Jane MacMaster

After one year or so delivering seminars that share practical techniques to help navigate complexity to public sector audiences, I’ve observed two simple and fundamental barriers to dealing more effectively with complex, interdisciplinary problems in the public sector.

First, is the lack of time to problem-solve – to pause and reflect on an issue, to build a deeper understanding of it, to think creatively about it from different angles, to think through some ideas, to test out some ideas. There is too much else going on.

Second, is that it’s often quite difficult to put one’s collective finger on what, exactly, the problem is.

Learning through modeling

October 9, 2023November 17, 2016

By Kirsten Kainz

How can co-creation communities use models – simple visual representations and/or sophisticated computer simulations – in ways that promote learning and improvement? Modeling techniques can serve to generate insights and correct misunderstandings. Are they equally as useful for fostering new learning and adaptation? Sterman (2006) argues that if new learning is to occur in complex systems then models must be subjected to testing. Model testing must, in turn, yield evidence that not only guides decision-making within the current model, but also feeds back evidence to improve existing models so that subsequent decisions can be based on new learning.

Consider the real-world case I was involved in of a meeting in a school district that intends to roll-out a new mathematics curriculum and support teachers’ use of the new curriculum through professional development. The district has made a large monetary investment in the curriculum and professional development both through the purchase of materials and the dedication of human resources to the effort.

The ‘methods section’ in research publications on complex problems – Purpose

September 5, 2024October 11, 2016

By Gabriele Bammer

Do we need a protocol for documenting how research tackling complex social and environmental problems was undertaken?

Usually when I read descriptions of research addressing a problem such as poverty reduction or obesity prevention or mitigation of the environmental impact of a particular development, I find myself frustrated by the lack of information about what was actually done. Some processes may be dealt with in detail, but others are glossed over or ignored completely.

For example, often such research brings together insights from a range of disciplines, but details may be scant on why and how those disciplines were selected, whether and how they interacted and how their contributions to understanding the problem were combined. I am often left wondering about whose job it was to do the synthesis and how they did it: did they use specific methods and were these up to the task? And I am curious about how the researchers assessed their efforts at the end of the project: did they miss a key discipline? would a different perspective from one of the disciplines included have been more useful? did they know what to do with all the information generated?

ICTAM: Bringing mental models to numerical models

August 24, 2022September 22, 2016

By Sondoss Elsawah

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.

Integration – Part 2: The “how”

September 5, 2024September 6, 2016

By Julie Thompson Klein

The “how” of integration focuses on pragmatics of process, with emphasis on methods. Toward that end, following the part 1 blog post on the “what” of integration, this blog post presents insights from major resources, with emphasis on collaborative research by teams.

Some widely used methods are well-known theories, for example general systems. Others are practiced in particular domains, such as integrated environmental assessment. Some utilize technologies, for example computer synthesis of data. And others, such as dialogue methods, target communication processes.

Making predictions under uncertainty

August 24, 2022August 25, 2016

By Joseph Guillaume

Prediction under uncertainty is typically seen as a daunting task. It conjures up images of clouded crystal balls and mysterious oracles in shadowy temples. In a modelling context, it might raise concerns about conclusions built on doubtful assumptions about the future, or about the difficulty in making sense of the many sources of uncertainty affecting highly complex models.

However, prediction under uncertainty can be made tractable depending on the type of prediction. Here I describe ways of making predictions under uncertainty for testing which conclusion is correct. Suppose, for example, that you want to predict whether objectives will be met. There are two possible conclusions – Yes and No, so prediction in this case involves testing which of these competing conclusions is plausible.

Tool users old and new: Why we need models

February 5, 2025June 23, 2016

By Suzanne A. Pierce

Ask most 21st century citizens whether they like technology and they will respond with a resounding, “Yes!” Ask them why and you’ll get answers like, “Because it’s cool and technology is fun!” or “Technology systems help us learn and understand things.” Or “Technology helps us communicate with one another, keep up with current events, or share what we are doing.” Look at the day-to-day activities of most people on the planet and you’ll find that they use some form of technology to complete almost every activity that they undertake.

When you think about it, technologies are really just tools. And we humans are tool users of old.

Serious gaming: Helping stakeholders address community problems

August 24, 2022June 9, 2016

By Nagesh Kolagani

Citizens are increasingly coming together to solve problems that affect their communities. Participatory modeling is a method that helps them to share their implicit and explicit knowledge of these problems with each other and to plan and implement mutually acceptable and sustainable solutions.

While using this method, stakeholders need to understand large amounts of information relating to these problems. Various interactive visualization tools are being developed for this purpose. One such tool is ‘serious gaming’ which combines technologies from the video game industry – mystery, appealing graphics, etc., – with a purpose other than pure entertainment, a serious, problem driven, educational purpose.

Playing Around with PARTICIPOLOGY

September 17, 2021June 7, 2016

By Alister Scott

Have you ever wanted a new way to engage with stakeholders that is more engaging, fun and effective? PARTICIPOLOGY is a set of open-access web resources and associated guidance that sets out to achieve these aims. It uses a board game format where players encounter questions and challenges as a dice throw dictates. The board, questions and rules of the game can be designed from scratch or existing templates can be adapted to the specific goals you have in mind. The game was designed to be used in participatory forums about land use options, but the principles can be more widely applied to all kinds of participatory processes.

There are five key findings from developing and using these resources.

Modeling as empowerment

August 24, 2022April 21, 2016

By Laura Schmitt Olabisi

Who can make systems change? The challenges of complexity are intensely felt by those who are trying to make strategic interventions in coupled human-environmental systems in order to fulfill personal, societal, or institutional goals. The activists, leaders, and decision-makers I work with often feel overwhelmed by trying to deal with multiple problems at once, with limited time, resources, and attention. We need tools to help leaders cut through the complexity so that they can identify the most effective strategies to make change.

This is where participatory system dynamics modelers like myself come in.